DOI QR코드

DOI QR Code

Estimation and Analysis of the Vertical Profile Parameters Using HeMOSU-1 Wind Data

HeMOSU-1 풍속자료를 이용한 연직 분포함수의 매개변수 추정 및 분석

  • Ko, Dong-Hui (Coastal Development and Ocean Energy Research Center, Korea Institute of Ocean Science and Technology) ;
  • Cho, Hong-Yeon (Marine Big-data Center, Korea Institute of Ocean Science and Technology, University of Science and Technology) ;
  • Lee, Uk-Jae (Department of Civil and Environmental Engineering, Wonkwang University)
  • 고동휘 (한국해양과학기술원 연안개발.에너지연구센터) ;
  • 조홍연 (한국해양과학기술원 해양빅데이터센터, 과학기술연합대학원 대학 KIOST SCHOOL) ;
  • 이욱재 (원광대학교 토목환경공학과)
  • Received : 2021.06.14
  • Accepted : 2021.06.21
  • Published : 2021.06.30

Abstract

A wind-speed estimation at the arbitrary elevations is key component for the design of the offshore wind energy structures and the computation of the wind-wave generation. However, the wind-speed estimation of the target elevation has been carried out by using the typical functions and their typical parameters, e.g., power and logarithmic functions because the available wind speed data is limited to the specific elevation, such as 2~3m, 10 m, and so on. In this study, the parameters of the vertical profile functions are estimated with optimal and analyzed the parameter ranges using the HeMOSU-1 platform wind data monitored at the eight different locations. The results show that the mean value of the exponent of the power function is 0.1, which is significantly lower than the typically recommended value, 0.14. The values of the exponent, the friction velocity, and the roughness parameters are in the ranges 0.0~0.3, 0~10 (m/s), and 0.0~1.0 (m), respectively. The parameter ranges differ from the typical ranges because the atmospheric stability condition is assumed as the neutral condition. To improve the estimation accuracy, the atmospheric condition should be considered, and a more general (non-linear) vertical profile functions should be introduced to fit the diverse profile patterns and parameters.

다양한 목표 고도에서의 풍속 추정은 해상풍력 구조물 설계 및 풍파 추정 등의 분야에서 매우 중요한 요소이다. 그러나 풍속 관측 자료가 특정 고도에 한정되어 있기 때문에 다른 고도에서의 풍속 추정은 일반적으로 사용되는 연직 분포함수와 평균적인 매개변수를 이용하여 추정한다. 본 연구에서는 HeMOSU-1 관측타워의 다양한 고도에서 측정한 풍속 자료를 이용하여 Power 함수, 대수함수의 매개변수를 추정하고 그 변동 양상을 분석하였다. 매개변수 추정 결과, Power 함수의 지수 매개변수는 일반적으로 제안되는 0.14(= 1/7) 보다 작은 평균 0.10 정도로 추정되었으며, 변동 범위도 0.0~0.3 정도로 파악되었다. 대수분포함수의 경우, 매개변수는 마찰속도와 조도 길이로 그 범위가 풍속에 따라 차이를 보이고 있으며, 변동 범위는 각각 0~10 (m/s), 0.0~1.0 (m) 정도로 파악되었으며, 일반적으로 제시되는 범위와는 그 차이를 보이는 것으로 파악되었다. 이러한 차이는 기존의 고도 분포함수가 대기 중립 조건을 가정하고 있는 영향으로 판단되며, 보다 정확한 추정을 위해서는 대기조건을 고려한 비선형 고도분포함수의 도입이 필요하다.

Keywords

Acknowledgement

본 연구는 산업통상자원부의 신재생에너지핵심기술개발 사업인 "해상 전주기 HSE 운영지원 모델 개발(과제번호: 20113040020010)"의 일환으로 수행되었습니다. 연구지원에 감사드립니다.

References

  1. Choi, H. and Kanda, J. (1990). Characteristics of the vertical wind profile for wind load estimation. J. of Wind Engineering, 45, 23-43. https://doi.org/10.5359/jawe.1990.45_23
  2. Coastal Engineering Manual (2008). Coastal Hydrodynamics (Part II), Part II-2 Meteorology and Wave Climate, EM 1110-2-1100, US Army Corps of Engineers (COE), Coastal Engineering Manual.
  3. Emeis, S. (2014). Review: Current issues in wind energy meteorology. Meteorological Applications, Royal Meteorological Society, 21, 803-819. https://doi.org/10.1002/met.1472
  4. Hsu, S.A. (1988). Coastal Meteorology, Chap. 6, Academic Press.
  5. Hsu, S.A., Meindl, E.A. and Gilhousen, D.B. (1994). Determining the power-law wind-profile exponent under near-neutral stability conditions at sea. Journal of Applied Meteorology, 33, 757. https://doi.org/10.1175/1520-0450(1994)033<0757:DTPLWP>2.0.CO;2
  6. Ko, D.H., Jeong, S.T., Cho, H., Kim, J.Y. and Kang, K.S. (2012). Error analysis on the Offshore Wind Speed Estimation using HeMOSU-1 Data. Journal of Korean Society of Coastal and Ocean Engineers, 24(5), 326-332 (in Korean). https://doi.org/10.9765/KSCOE.2012.24.5.326
  7. Kim, J.Y. and Kim, M.S. (2017). A comparison of offshore metmast and lidar wind measurements at various heights. Journal of Korean Society of Coastal and Ocean Engineers, 29(1), 12-19 (in Korean). https://doi.org/10.9765/KSCOE.2017.29.1.12
  8. Kim, D.H., Lee, G.N. and Kwon, O.S. (2013). Prediction of Wind Power Generation using HeMOSU-1 Data, Asia-Pacific Forum on Renewable Energy (AFORE), 246.
  9. Lee, G.M., Kim, D.H. and Kwon, O. (2014). Prediction of Wind Power Generation at Southwest Coast of Korea considering Uncertainty of HeMOSU-1 Wind Speed Data. New and Renewable Energy, 10(2), 19-28 (in Korean). https://doi.org/10.7849/ksnre.2014.10.2.019
  10. Mwanyika, H.H. and Kainkwa, R.M. (2006). Determination of the power law exponent for southern highlands of tanzania. Tanzania Journal of Science, 32, 103-107.
  11. Molina-Garcia, A., Fernandez-Guillamon, A., Gomez-Lazaro, E., Honrubia-Escribano, A. and Bueso, M.C. (2019). Vertical wind profile characteriazation and identification of patterns based on a shape clustering algorithm, 7, 30890-30904, IEEE Access, DOI 10.1109/ACCESS.2019.2902242.
  12. Moller, M., Domagalski, P. and Saetarn, L.R. (2019). Characteristics of abnormal vertical wind profiles at a coastal site. J. of Physics: Conference Series 1356 (the 16th Deep Sea Offshore Wind R&D Conference), 012030. DOI 10.1088/1742-6596/1356/1/012030.
  13. Pena, A., Gryning, S.E. and Hasager, C.B. (2008). Measurements and Modelling of the Wind Speed Profile in the Marine Atmospheric Boundary Layer. Boundary-Layer Meteorology, 129, 479-495, DOI 10.1007/s10546-008-9323-9.
  14. Sozzi, R., Rossi, F. and Georgiadis, T. (2001). Parameter estimation of surface layer turbulence from wind speed vertical profile. Environmental Modelling and Software, 16, 73-85. https://doi.org/10.1016/S1364-8152(00)00066-9